For every patient, nowadays, dentists use a software to generate the dental scheme. The dental scheme is basically a diagram representing the whole dentition of the patient. On this diagram, each tooth is represented along with the various operations the patient underwent. The dental scheme for instance shows whether some teeth are missing, or if any treatment was ever performed on the dental roots, it also represents the dental fillings, removable prosthesis, dental crowns or tooth bridges. Filling up the dental scheme may be tedious for dentists, as for every new patient, they would have to carefully make an inventory of every dental care the patient underwent. In this work, we intend to study the feasibility of automatically generating the dental scheme from radiographs. Indeed, we aim to propose an image processing method that would automatically detect missing teeth, as well as any dental care in the dentition, this may save a significant amount of time during the dental consultation. In a first step, our method extracts the relevant portion of the scanner image, i.e. we automatically crop the dentition and thus remove the jaws and chin. The bending of the jaw (dentition curvature) is also estimated, and allows to distinguish the upper and lower jaws. A local minimum/maximum computation coupled with the Hough transform, and a fit with Gaussian Mixture Models helps us to segment the teeth despite strong luminance irregularities due to the imaged spine.